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The study of biodiversity started as a single unified field that spanned both ecology and evolution and both macro and micro phenomena. But over the 20th century, major trends drove ecology and evolution apart and pushed an emphasis towards the micro perspective in both disciplines. Macroecology and macroevolution re‐emerged as self‐consciously distinct fields in the 1970s and 1980s, but they remain largely separated from each other. Here, we argue that despite the challenges, it is worth working to combine macroecology and macroevolution. We present 25 fundamental questions about biodiversity that are answerable only with a mixture of the views and tools of both macroecology and macroevolution. [ABSTRACT FROM AUTHOR]

Aim: To quantify the influence of past archipelago configuration on present‐day insular biodiversity patterns, and to compare the role of long‐lasting archipelago configurations over the Pleistocene to configurations of short duration such as at the Last Glacial Maximum (LGM) and the present‐day. Location: 53 volcanic oceanic islands from 12 archipelagos worldwide—Azores, Canary Islands, Cook Islands, Galápagos, Gulf of Guinea, Hawaii, Madeira, Mascarenes, Pitcairn, Revillagigedo, Samoan Islands and Tristan da Cunha. Time period: The last 800 kyr, representing the nine most recent glacial–interglacial cycles. Major taxa studied: Land snails and angiosperms. Methods: Species richness data for land snails and angiosperms were compiled from existing literature and species checklists. We reconstructed archipelago configurations at the following sea levels: the present‐day high interglacial sea level, the intermediate sea levels that are representative of the Pleistocene and the low sea levels of the LGM. We fitted two alternative linear mixed models for each archipelago configuration using the number of single‐island endemic, multiple‐island endemic and (non‐endemic) native species as a response. Model performance was assessed based on the goodness‐of‐fit of the full model, the variance explained by archipelago configuration and model parsimony. Results: Single‐island endemic richness in both taxonomic groups was best explained by intermediate palaeo‐configuration (positively by area change, and negatively by palaeo‐connectedness), whereas non‐endemic native species richness was poorly explained by palaeo‐configuration. Single‐island endemic richness was better explained by intermediate archipelago configurations than by the archipelago configurations of the LGM or present‐day. Main conclusions: Archipelago configurations at intermediate sea levels—which are representative of the Pleistocene—have left a stronger imprint on single‐island endemic richness patterns on volcanic oceanic islands than extreme archipelago configurations that persisted for only a few thousand years (such as the LGM). In understanding ecological and evolutionary dynamics of insular biota it is essential to consider longer‐lasting environmental conditions, rather than extreme situations alone. [ABSTRACT FROM AUTHOR]

Abstract: Motivation: Past sea level fluctuations have shaped island area and archipelago configuration. The availability of global high‐resolution data on bathymetry and past sea levels allows reconstruction of island palaeo‐geography. Studies on the role of palaeo‐area often consider only the Last Glacial Maximum, which neglects the dynamics of island fusion and fission resulting from cyclic sea level fluctuations throughout the Quaternary. Currently, no global database is available to test the role of changing island geographies driven by Quaternary sea level change on evolutionary, ecological and archaeological patterns. However, data on island palaeo‐environments is crucial for understanding insular biodiversity distributions and human settlement patterns. Here, we present the Palaeo‐Islands and Archipelago Configuration (PIAC) database, containing sea level‐driven palaeo‐geography changes over the late Quaternary of 178 islands in 27 archipelagos, and discuss its relevance, limitations and uncertainties. The R functions developed to create the PIAC database are provided to allow calculations for other islands, time steps, sea‐level curves and higher spatio‐temporal resolutions. Main types of variables contained: Polygon shapefiles with archipelago configuration and tables with palaeo‐area per island. Spatial location and grain: The database has a global representation, with 27 archipelagos being covered: Aldabra, Azores, Balearic Islands, California Channel Islands, Canary Islands, Cape Verde, Comoros, Cook Islands, Crozet Islands, Dutch Caribbean, Galápagos, Gulf of Guinea, Hawaii, Inner Seychelles, Juan Fernández, Kuril Islands, Madeira, Marianas, Marquesas, Mascarenes, Phoenix Islands, Pitcairn Islands, Prince Edward Islands, Revillagigedo, Samoan Islands, Society Islands and Tristan da Cunha. All data are at 1 km2 spatial resolution. Time period and grain: The focus of this paper is on the last 35 kyr; data for the last 140 kyr are also provided. The grain is 1 kyr temporal resolution. Level of measurement: Data are per island, grouped per archipelago. Software format: The data were produced in the R programming language. [ABSTRACT FROM AUTHOR]

Aim Higher-elevation areas on islands and continental mountains tend to be separated by longer distances, predicting higher endemism at higher elevations; our study is the first to test the generality of the predicted pattern. We also compare it empirically with contrasting expectations from hypotheses invoking higher speciation with area, temperature and species richness. Location Thirty-two insular and 18 continental elevational gradients from around the world. Methods We compiled entire floras with elevation-specific occurrence information, and calculated the proportion of native species that are endemic ('percent endemism') in 100-m bands, for each of the 50 elevational gradients. Using generalized linear models, we tested the relationships between percent endemism and elevation, isolation, temperature, area and species richness. Results Percent endemism consistently increased monotonically with elevation, globally. This was independent of richness-elevation relationships, which had varying shapes but decreased with elevation at high elevations. The endemism-elevation relationships were consistent with isolation-related predictions, but inconsistent with hypotheses related to area, richness and temperature. Main conclusions Higher per-species speciation rates caused by increasing isolation with elevation are the most plausible and parsimonious explanation for the globally consistent pattern of higher endemism at higher elevations that we identify. We suggest that topography-driven isolation increases speciation rates in mountainous areas, across all elevations and increasingly towards the equator. If so, it represents a mechanism that may contribute to generating latitudinal diversity gradients in a way that is consistent with both present-day and palaeontological evidence. [ABSTRACT FROM AUTHOR]

Aim We explore the island species-area relationships ( ISARs) of several plant groups differing in dispersal ability. We examine whether: (i) the ISAR slope is higher for less dispersive groups (diminishing from not-wind-dispersed seed plants to wind-dispersed seed plants, pteridophytes and bryophytes); and (ii) the regional richness is higher than that predicted by the ISAR of its constituent islands for groups with lower dispersal ability. Additionally, we relate both patterns to the compositional dissimilarity (beta diversity) between islands. Location The Macaronesian archipelagos of the Azores, Madeira and Canary Islands. Methods ISARs were estimated using the conventional power model. Differences in slopes among taxa were analysed through ANCOVA tests. We assessed the deviation of the total richness of the Macaronesian flora from that predicted by the ISAR and calculated several measures of beta diversity (turnover, nestedness-resultant dissimilarity and nestedness). Analyses were repeated after excluding the two Canarian islands of Lanzarote and Fuerteventura, which have unique climatic and geological conditions in the region. Results All ISAR models were significant except for pteridophytes (for which it was significant when excluding Lanzarote and Fuerteventura). ISAR slopes did not differ among taxa. Regional richness followed ISAR predictions for bryophytes and pteridophytes when Lanzarote and Fuerteventura were excluded, while the total number of Macaronesian seed plants (particularly not-wind-dispersed species) always fell above the ISAR. Turnover was higher in seed plants than in bryophytes and pteridophytes, and the opposite occurred with nestedness. Main conclusions Differences in dispersal ability influence the compositional dissimilarity between these islands, but not the rate of species increase with area. This may be because ISAR slopes are mostly determined by within-island processes of species accumulation, while differences in dispersal generate different between-island patterns. The lack of relationship between the ISAR slope and species replacement or nestedness prevents its use as a proxy for beta diversity. [ABSTRACT FROM AUTHOR]

Aim To establish the extent to which archipelagos follow the same species–area relationship as their constituent islands and to explore the factors that may explain departures from the relationship. Location Thirty-eight archipelagos distributed worldwide. Methods We used ninety-seven published datasets to create island species–area relationships (ISARs) using the Arrhenius logarithmic form of the power model. Observed and predicted species richness of an archipelago and of each of its islands were used to calculate two indices that determined whether the archipelago followed the ISAR. Archipelagic residuals ( ArcRes) were calculated as the residual of the prediction provided by the ISAR using the total area of the archipelago, standardized by the total richness observed in the archipelago. We also tested whether any characteristic of the archipelago (geological origin and isolation) and/or taxon accounts for whether an archipelago fits into the ISAR or not. Finally, we explored the relationship between ArcRes and two metrics of nestedness. Results The archipelago was close to the ISAR of its constituent islands in most of the cases analysed. Exceptions arose for archipelagos where (i) the slopes of the ISAR are low, (ii) observed species richness is higher than expected by the ISAR and/or (iii) distance to the mainland is small. The archipelago's geological origin was also important; a higher percentage of oceanic archipelagos fit into their ISAR than continental ones. ArcRes indicated that the ISAR underpredicts archipelagic richness in the least isolated archipelagos. Different types of taxon showed no differences in ArcRes. Nestedness and ArcRes appear to be related, although the form of the relationship varies between metrics. Main conclusions Archipelagos, as a rule, follow the same ISAR as their constituent islands. Therefore, they can be used as distinct units themselves in large-scale biogeographical and macroecological studies. Departure from the ISAR can be used as a crude indicator of richness-ordered nestedness, responsive to factors such as isolation, environmental heterogeneity, number and age of islands. [ABSTRACT FROM AUTHOR]